1. Field
Aspects of the present invention generally relate to electric vehicles and more specifically relates to smart electrical charging stations or systems for charging electric vehicles.
2. Description of the Related Art
With the advent of high fuel prices, the automotive industry has reacted with a selection of Electric Vehicles (EVs). Such EVs are propelled by an electric motor (or motors) that are powered by rechargeable power sources (e.g., battery packs). EVs include both full electric and hybrid electric vehicles. Electric motors have several advantages over internal combustion engines. For example, electric motors may convert about 75% of the chemical energy from the batteries to power the wheels, whereas internal combustion engines (ICES) may only convert only about 20% of the energy stored in gasoline. EVs emit no tailpipe pollutants when operating in battery mode. Electric motors provide quiet, smooth operation, strong acceleration and require relatively low maintenance. However, most EVs can only go about 100-200 miles before requiring recharging. Fully recharging an EV's battery pack may take 3 to 8 hours. Even a quick charge to about 80% capacity can take about 30 minutes. Furthermore, as battery pack size increases, so does the corresponding charging time. EV charging may take place at the owner's residence using an electric vehicle recharging station, referred to herein as an electric vehicle supply equipment (EVSE). Such EVSEs are typically installed at the residence (e.g., in a garage), and are electrically coupled to the electrical load center for the residence.
Electric vehicle charging is a high power, high energy load that can be shaped or shifted for economic, grid, or societal benefit. The shaping of an electric vehicle's charging load is based on some basic operating conditions surrounding of en electric vehicle and its charging equipment. The most popular EVs on the road today have a wide array of battery sizes ranging from 4 to 85 kWhrs. Battery size has a significant impact on the estimation of the cumulative kWhr demand for EVs; the bigger the battery, the further EV drivers can commute in all electric mode and therefore the larger the amount of energy that needs to be refilled at night. The second factor is the EV's built-in ability to receive electricity which is measured by the size of its inverter. Common inverter sizes range from 3 to 6.6 kW with some select vehicles capable of 10-20 kW. Commonly, EVs with larger battery packs require larger inverters to keep the recharge time to a minimum, causing EVs with larger inverter capability to potentially represent a much larger, faster charging load than EVs with smaller inverter capabilities. The third factor is the maximum charging rate of the charging equipment (EVSE) for the vehicle, varying again widely between what are commonly referred to as Level I and Level II chargers. Most vehicles come equipped with a 120 V AC Level I charger which ranges from 1.2-2.6 kW of charging rate. The majority of EV owners purchase a Level 2 charger in order to maximize the investment in an EV by maximizing the amount of time they are able to drive in full electric mode. Most Level II chargers range from 3.3 to 7.2 kW, with a few models matched to the vehicles that can receive 10-20 kW. For energy demand planning, the lowest size dictates the charging rate. For example, an EV with an inverter capability of 6.6 KW which is being charged by a 3.3 kW charging station will only be capable of drawing a peak charge of 3.3 kW. Given these basic figures, it is easy to illustrate that at a full charging rate of 6.6 kW it is highly feasible to full charge a 24 kW EV between the hours of 1 AM-5 AM if charging at a full rate of 6.6 kW or to full charge an electric vehicle between 9 PM-5 AM at a rate of 3 kW/hour.
In prior technologies, the electric vehicle charging process is either 1) lacking intelligence, 2) possesses intelligence but only to run automated schedules, or 3) has intelligence to control the charging process based on a utility or asset owner controlling when the charging process is available—typically driven by a basic user profile or payment management. With a lack of intelligence, significant swings in the energy consumption of electric vehicles are possible (resulting in challenges for grid operators). Charging profiles based on schedules help address this issue, but are limited to scenarios where the ideal solution is simply to shift the load (shifting/shaping of the load is problematic in a scheduling scenario where future demand is not known). Furthermore, charging schedules are often not properly configured by end users resulting in non-optimum performance. Finally user profile/payment management systems limit the actions to demand response events or requests where a utility takes direct action on the charging system—the downside to these methods is that they are coarsely applied throughout a network, lack user feedback, and result in an inconvenience for the end user.
Therefore, there is a need for improvements to EVSE systems, such as residential EVSE systems including EVSE charging stations configured to electrically connect to an EV.